# -*- coding: UTF-8 -*-

import numpy as np
import matplotlib.pyplot as plt
from sklearn.preprocessing import StandardScaler
from keras.models import Sequential
from keras.layers import Dense

filepath = '/home/zxl/zy/Predict_Module/Data/RUL_Turbofan/train_FD001.txt'
data = np.loadtxt(filepath)  # (20631, 26)

data_features = data[847:1116, [0, 1, 2, 3, 4, 6, 7, 8, 11, 12, 13]]  # (20631, 5+6) 5#发动机
# print data_features
data_5 = data_features[:, 5:]  # (20631, 6)
scalar = StandardScaler()  # z-score
data_5_x = scalar.fit_transform(data_5)  # (269, 6)

# plt.plot(data_5_f1) 
# plt.savefig('/home/zxl/zy/Predict_Module/Data/RUL_Turbofan/data_5_f1.png')

